How to train a LSTM model with multi dimensional data
LSTM can be tricky, I'll give my $0.02.
LSTM input layer defines the shape so it would be something like this.
If I am understanding your question correctly, your data can be framed as 184 samples with 2 time steps and 70 features?
So the start of the code might look like this.
model = Sequential()
model.add(LSTM(184, input_shape=(50, 2)))